Short Sales and Trade Classification Algorithms
AbstractThis paper demonstrates that short sales are often misclassified as buyer-initiated by the Lee-Ready and other commonly used trade classification algorithms. This result is due in part to regulations which require short sales be executed on an uptick or zero-uptick. In addition, while the literature considers "immediacy premiums" in determining trade direction, it ignores the often larger borrowing premiums which short sellers must pay. Since short sales constitute approximately 30% of all trade volume on U.S. exchanges, these results are important to the empirical market microstructure literature as well as to measures that rely upon trade classification, such as the probability of informed trading (PIN) metric.
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Bibliographic InfoPaper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 14158.
Date of creation: Jul 2008
Date of revision:
Publication status: published as Asquith, Paul & Oman, Rebecca & Safaya, Christopher, 2010. "Short sales and trade classification algorithms," Journal of Financial Markets, Elsevier, vol. 13(1), pages 157-173, February.
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Find related papers by JEL classification:
- G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
- G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation
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